Sign Language Digits

Sign Language Digits

Sign languages are languages that can include simultaneously employing hand gestures, movement, the orientation of the fingers, arms or body, and facial expressions to convey a speaker's ideas [1]. In this article, we develop a stacking classifier model from various scikit-learn classifiers for the Sign Language Digits dataset from Kaggle. The main purpose of this article is to demonstrate implementation of stacking classifiers.

Dataset

Investigating the data, we can see that y represent numbers 0 to 9 that encoded into dummy variables.

Train and Test sets

StratifiedKFold is a variation of k-fold which returns stratified folds: each set contains approximately the same percentage of samples of each target class as the complete set.

Modeling: CatBoost Classifier

CatBoost Classifier is based on gradient boosted decision trees. During training, a set of decision trees is built consecutively. Each successive tree is built with reduced loss compared to the previous trees.

The best result for each metric calculated on each validation dataset.


References

  1. Sign language Wikipedia Page
  2. Sign Language Digits Dataset
  3. CatBoost Classifier Documentation